Velo-cardio-facial syndrome and DiGeorge syndrome are relatively common disorders and affect at least 1/4000 newborn children. Most of the cases of VCFS/DGS are sporadic. Children with these syndromes present with a number of abnormalities including facial dysmorphology, cardiovascular defects, immune defects, speech defects and learning disabilities. As the children grow older, many of them develop severe psychiatric illness. A subset of the patients diagnosed to have VCFS/DGS have a deletion of either 1.5 or 3.0 Mb of DNA on human chromosome 22ql 1. The phenotypes associated with VCFS/DGS are quite variable. Individuals within the same family who carry the same deletion sometimes have different phenotypic manifestations. Because of the variability in the phenotypic spectrum and since not all cases may result from abnormalities in chromosome 22 there is a strong need to develop quantitative clinical criteria for VCFS/DGS diagnosis. It is also possible that a careful clinical data acquisition would allow us to classify and sub classify the patient population. Many of the organs systems affected in VCFS/DGS patients have their origin in the neural crest. This includes the face. Although it is well recognized that facial dysmorphology is an important component of VCFS/DGS phenotype no good quantitative criteria for describing the facial dysmorphology are available. We propose to use an emerging method of three-dimensional photogrammetry to collect information about the facial features of patients clinically diagnosed to have VCFS/DGS. This method is rapid, analogous to taking a photograph, and provides a digitized three-dimensional image of the face of an individual. Software programs written by our colleagues and applied by us allow a large number of measurements that are accurate and reproducible. During the three-year period, we will enroll 300 patients in the study and obtain photogrammetric measurements as well as other clinical parameters from these patients. We hypothesize that facial features can be used as accurate diagnostic measures of these syndromes and that they would correlate with the deletion status and the size of the Ideletion. We have assembled a group of clinical and basic scientists as well a bioinformatician to address this problem.